• 设为首页
  • 点击收藏
  • 手机版
    手机扫一扫访问
    迪恩网络手机版
  • 关注官方公众号
    微信扫一扫关注
    公众号

google/applied-machine-learning-intensive: Applied Machine Learning Intensive

原作者: [db:作者] 来自: 网络 收藏 邀请

开源软件名称(OpenSource Name):

google/applied-machine-learning-intensive

开源软件地址(OpenSource Url):

https://github.com/google/applied-machine-learning-intensive

开源编程语言(OpenSource Language):

Jupyter Notebook 99.8%

开源软件介绍(OpenSource Introduction):

Applied Machine Learning Intensive

Overview

The Applied Machine Learning Intensive (AMLI) is a collection of content that can be used to teach machine learning. The original content was created for a 10-week, bootcamp-style course for undergraduate college students. Designed for students who weren’t necessarily majoring in computer science, the goal was to enable participants to apply machine learning to different fields using high-level tools.

The content primarily consists of slides, Jupyter notebooks, and facilitator guides. The slide decks are written in marp markdown syntax, which can be exported to other formats. The Jupyter notebooks were written in and targeted to run in Colab. The instructor guide as an odt document.

Answer Keys

Applied Machine Learning Intensive instructional materials are available open source for faculty looking to run this program for students. This repository offers all slide decks, facilitation guides, labs, and gradable items. Because the program is considered academic in nature, we ask that interested faculty fill out the form below to receive a password to unlock the answer keys. We will provide you with a password that can be used to unlock the keys using a standard zip program or the tools/unlock_labs.py tool found in this repository.

Please fill out the following brief form to receive the answer keys for the curriculum:

https://docs.google.com/forms/d/e/1FAIpQLSd9v0az2wmKP659Xx5SlS7WPbQPD3u3yLXZMn0LHf3Vjj-ziw/viewform

The information that you submit will be maintained in accordance with Google’s Privacy Policy.

Licensing Information

All course content (Colabs, slides, guides, and materials) are open sourced under the CC-BY-4.0 International license. All code contained in this course is open sourced under the Apache 2.0 license.

Attribution and license information for content not created by Google will be presented in the speaker notes.




鲜花

握手

雷人

路过

鸡蛋
该文章已有0人参与评论

请发表评论

全部评论

专题导读
热门推荐
阅读排行榜

扫描微信二维码

查看手机版网站

随时了解更新最新资讯

139-2527-9053

在线客服(服务时间 9:00~18:00)

在线QQ客服
地址:深圳市南山区西丽大学城创智工业园
电邮:jeky_zhao#qq.com
移动电话:139-2527-9053

Powered by 互联科技 X3.4© 2001-2213 极客世界.|Sitemap